We study the robustness of block resampling procedures for time series. We first derive a set of formulas to quantify … their quantile breakdown point. For the block bootstrap and the sub- sampling, we find a very low quantile breakdown point …. A similar robustness problem arises in relation to data-driven methods for selecting the block size in applications …

regression model. Monte Carlo simulations in two settings where the bootstrap fails show the accuracy and robustness of the …We characterize the robustness of subsampling procedures by deriving a formula for the breakdown point of subsampling … can be applied instead. To overcome these robustness problems, we introduce a consistent robust subsampling procedure for …

In this paper we analyse bootstrap procedures for systems cointegration tests with a prior adjustment for deterministic … the bootstrap test procedures are derived and their small sample properties are studied. The simulation study also …

In this paper we analyse bootstrap procedures for systems cointegration tests with a prior adjustment for deterministic … the bootstrap test procedures are derived and their small sample properties are studied. The simulation study also …

bootstrap to achieve valid inference in a time series setting. The test statistics and the estimators are computed using linear …

The standard confidence regions based on the first-order approximation of quantile regression estimators can be … sample size. We further extend these results to censored quantile regression models. Our results are extensions of the … previous results of Chen and Hall (1993) to the regression contexts. Also, from the duality of confidence regions and …

appropriate p-value for a test for hysteresis we propose two alternative bootstrap procedures: the first is valid under … homoskedastic errors and the second allows for general heteroskedasticity. We investigate the performance of both bootstrap …